A key selling point for any communications system is the peak data rate it can deliver. For wireless communications systems employing channel coding, peak data rates imply little or no effective coding. When channel coding is weak, a wireless receiver relies on equalization to suppress the interference caused by inter-symbol interference (ISI). Equalizers typically suppress interference sufficiently to achieve peak data rates only for flat or very lightly dispersive channels. For a CDMA system, experience has shown that equalizer tap placement is critical for dispersive channels. CDMA equalizers can be either chip level or symbol level. An equalizer tap can therefore correspond to an element of a Finite Impulse Response (FIR) filter (chip level) or a receiver finger (symbol level).
The typical goal of a CDMA receiver is to collect the energy from (multipath) signal echoes and add them coherently. To achieve this goal, the receiver attempts to: (1) estimate the number of (significant) signal echoes and the delay of each echo; (2) despread the signal for each echo delay; (3) compute combining weights for each signal echo; and (4) combine the despread traffic data obtained from the echoes using the combining weights, to demodulate the transmitted data.
The above list is an outline of a receiver architecture referred to as “despread and combine.” This type of architecture encompasses both Rake and Generalized Rake (G-Rake) approaches. As noted above, the scenario of interest is the flat (or one path) case. Here the receiver would like to perform despreading at the exact delay of the signal path. However, in typical receivers, samples are only available at certain time values, which may not include the exact path delay. In point-to-point systems with sufficient channel coding, this is not a concern, as sampling close to but not at the true delay incurs only a minor penalty in signal power.
If the main limitation is thermal noise, then the noise power is independent of the delay used. However, when high data rates (with little or no channel coding) are used, such as in High Speed Packet Access (HSPA) in Wideband CDMA (WCDMA), the main limitation is self-interference. Data is sent in parallel using different spreading waveforms. These waveforms are orthogonal if the receiver samples the signal at the true path delay. Otherwise, the orthogonality property is lost. The impact on performance can be dramatic at very high data rates because the channel coding cannot correct errors introduced by self-interference.
Performance therefore can be highly sensitive to which time samples are available at the receiver. In traditional receiver architectures, an arbitrary sampling phase is used to start generating samples. Due to frequency offset errors and the imperfection of the sampling clock, the sampling phase drifts in time. Thus, while it might sample exactly at the true path at one moment in time, it will eventually not sample at the true path delay.
The severity of the problem is directly proportional to the resolution used in delay estimation, for path searching. Typically, delay estimation employs a regularly spaced raster from which it chooses delay values for the echoes of the transmitted signal. For a flat channel, the inherent raster-nature of delay estimation can cause estimation errors.
More broadly, misalignment of actual path(s) with sampling intervals can cause demodulation problems in multiple ways. For example, it is entirely possible that a delay estimator may incorrectly report two (or more) paths due to misalignment. In this case the receiver will assign multiple fingers to incorrect processing delays, and peak data rates will not be achieved.
With these issues in mind, a symbol level equalizer performs the following actions: (1) performs path search; (2) estimates path delays; (3) assigns fingers based on path delays; (4) despreads received signals for assigned fingers; (5) computes combining weights given finger delays; and (6) combines despread values. Here, step (3) is the key to mitigating the effects of frequency error and timing drift. A conventional mitigation approach involves assigning fingers to the delays reported by the delay estimator as well as other delays selected to improve equalization performance—see U.S. Pat. No. 6,922,434 to Wang et al.
This conventional approach may not work well for flat channels with frequency error and timing drift. The use of a delay placement grid may, in at least some instances, improve demodulation. See, for example, U.S. Pub. 2006/0268962 A1 to Cairns et al. However, in some scenarios, the use of delay grid to place a limited number of fingers or filter taps does not work as well. There is the possibility to monitor the delays as reported by a path searcher. For example, if the path searcher indicates a single path (per antenna), the channel is considered to be flat. Otherwise, the channel is considered dispersive. In another approach, the receiver may maintain a metric related to the dispersiveness of a wireless channel, and use it to control the spacing and extent of a grid of fingers. See, for example, U.S. patent application Ser. No. 12/408,939 to Cairns, filed Mar. 23, 2009, and entitled “Signal Reception with Adjustable Processing Delay Placement.”
However, one problem with using the delay(s) reported by the path searcher is that the delays can be unreliable. Spurious delays can (and are) reported for a flat channel. Alternatively, delays can be missed for dispersive channels. Both types of errors cause unreliable grid activation, which leads to degraded performance. Nor does the use of a dispersiveness metric such as discussed above provide a solution to the problem.